日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Publisher Correction: Ultra-high gradient connectomics and microstructure MRI scanner for imaging of human brain circuits across scales

出版商更正:用于跨尺度成像人类大脑回路的超高梯度连接组学和微结构磁共振成像扫描仪

Ramos-Llordén, Gabriel; Lee, Hong-Hsi; Davids, Mathias; Dietz, Peter; Krug, Andreas; Kirsch, John E; Mahmutovic, Mirsad; Müller, Alina; Ma, Yixin; Lee, Hansol; Maffei, Chiara; Yendiki, Anastasia; Bilgic, Berkin; Park, Daniel J; Tian, Qiyuan; Clifford, Bryan; Lo, Wei-Ching; Stocker, Stefan; Fischer, Jasmine; Ruyters, Gudrun; Roesler, Manuela; Potthast, Andreas; Benner, Thomas; Rummert, Elmar; Schuster, Rebecca; Basser, Peter J; Witzel, Thomas; Wald, Lawrence L; Rosen, Bruce R; Keil, Boris; Huang, Susie Y

Ultra-high gradient connectomics and microstructure MRI scanner for imaging of human brain circuits across scales

用于跨尺度成像人类大脑回路的超高梯度连接组学和微结构磁共振成像扫描仪

Ramos-Llordén, Gabriel; Lee, Hong-Hsi; Davids, Mathias; Dietz, Peter; Krug, Andreas; Kirsch, John E; Mahmutovic, Mirsad; Müller, Alina; Ma, Yixin; Lee, Hansol; Maffei, Chiara; Yendiki, Anastasia; Bilgic, Berkin; Park, Daniel J; Tian, Qiyuan; Clifford, Bryan; Lo, Wei-Ching; Stocker, Stefan; Fischer, Jasmine; Ruyters, Gudrun; Roesler, Manuela; Potthast, Andreas; Benner, Thomas; Rummert, Elmar; Schuster, Rebecca; Basser, Peter J; Witzel, Thomas; Wald, Lawrence L; Rosen, Bruce R; Keil, Boris; Huang, Susie Y

Corrigendum to "Deep learning in fetal, infant, and toddler neuroimaging research"[Dev. Cognit. Neurosci. (2026), 101680]

对“胎儿、婴儿和幼儿神经影像学研究中的深度学习”的更正[Dev. Cognit. Neurosci. (2026), 101680]

Chin, Jenna H; Wyburd, Madeleine K; Ayzenberg, Vladislav; Bayet, Laurie; Bilgic, Berkin; Chen, Emily M; Chen, Yuting; Dineen, Áine; Fujita, Shohei; Liu, Janelle; Jun, Yohan; Camacho, M Catalina; Zöllei, Lilla

Deep learning in fetal, infant, and toddler neuroimaging research

深度学习在胎儿、婴儿和幼儿神经影像学研究中的应用

Chin, Jenna H; Wyburd, Madeleine K; Ayzenberg, Vladislav; Bayet, Laurie; Bilgic, Berkin; Chen, Emily M; Chen, Yuting; Dineen, Áine; Fujita, Shohei; Liu, Janelle; Jun, Yohan; Camacho, M Catalina; Zöllei, Lilla

Highly Reproducible, Vendor-Agnostic, Motion-Insensitive Liver PDFF Mapping at 0.55T, 1.5T, and 3T

在 0.55T、1.5T 和 3T 磁场强度下,实现了高度可重复、与厂商无关、运动不敏感的肝脏 PDFF 映射。

Tang, Jiayi; Tamada, Daiki; Nielsen, Jon-Fredrik; Starekova, Jitka; Heidenreich, Julius F; Schön, Felix; Anagnostopoulos, Alexandra A; Roshanshad, Amirhossein; Mao, Lu; Fujita, Shohei; Xu, Pengcheng; Keen, Christopher; Shaik, Imam Ahmed; Milshteyn, Eugene; Yee, Seonghwan; Ellison, Andrew J; Rutkowski, David; Kammerman, Jeff; Brittain, Jean H; Zhong, Xiaodong; Grissom, William A; Zaitsev, Maxim; Carrel, Aaron L; Rathi, Yogesh; Jiang, Yun; Bilgic, Berkin; Reeder, Scott B; Hernando, Diego

Learning to simulate realistic human diffuse reflectance spectra

学习模拟真实的人体漫反射光谱

Hübner, Marco; Bin Qasim, Ahmad; Studier-Fischer, Alexander; Rees, Maike; Tran Ba, Viet; Nölke, Jan-Hinrich; Seidlitz, Silvia; Sellner, Jan; Heinecke, Janne; Brandt, Jule; Özdemir, Berkin; Dreher, Kris; Seitel, Alexander; Nickel, Felix; Max Haney, Caelan; Kowalewski, Karl-Friedrich; Ayala, Leonardo; Maier-Hein, Lena

Erratum: Learning to simulate realistic human diffuse reflectance spectra (Erratum)

勘误:学习模拟真实的人体漫反射光谱(勘误)

Hübner, Marco; Bin Qasim, Ahmad; Studier-Fischer, Alexander; Rees, Maike; Tran Ba, Viet; Nölke, Jan-Hinrich; Seidlitz, Silvia; Sellner, Jan; Heinecke, Janne; Brandt, Jule; Özdemir, Berkin; Dreher, Kris; Seitel, Alexander; Nickel, Felix; Max Haney, Caelan; Kowalewski, Karl-Friedrich; Ayala, Leonardo; Maier-Hein, Lena

The relationship between first trimester maternal diet and early pregnancy loss: a retrospective case-control study

孕早期母亲饮食与早期妊娠丢失的关系:一项回顾性病例对照研究

Varol, Muhammed Bartu; Özyilmaz Kircali, Berkin

Noise2Average: An iterative residual learning strategy for image denoising without clean data

Noise2Average:一种无需干净数据即可进行图像去噪的迭代残差学习策略

Li, Zihan; Li, Ziyu; Bilgic, Berkin; Ying, Kui; Salat, David H; Polimeni, Jonathan R; Liao, Hongen; Huang, Susie Y; Tian, Qiyuan

Accurate prediction of disease-risk factors from volumetric medical scans by a deep vision model pre-trained with 2D scans

利用预先用二维扫描数据训练的深度视觉模型,从体积医学扫描数据中准确预测疾病风险因素

Avram, Oren; Durmus, Berkin; Rakocz, Nadav; Corradetti, Giulia; An, Ulzee; Nittala, Muneeswar G; Terway, Prerit; Rudas, Akos; Chen, Zeyuan Johnson; Wakatsuki, Yu; Hirabayashi, Kazutaka; Velaga, Swetha; Tiosano, Liran; Corvi, Federico; Verma, Aditya; Karamat, Ayesha; Lindenberg, Sophiana; Oncel, Deniz; Almidani, Louay; Hull, Victoria; Fasih-Ahmad, Sohaib; Esmaeilkhanian, Houri; Cannesson, Maxime; Wykoff, Charles C; Rahmani, Elior; Arnold, Corey W; Zhou, Bolei; Zaitlen, Noah; Gronau, Ilan; Sankararaman, Sriram; Chiang, Jeffrey N; Sadda, Srinivas R; Halperin, Eran